WHY?

In image captioning or visual question answering, the features of an image are extracted by the spatial output layer of pretrained CNN model.

WHAT?

This paper suggests bottom-up attention using object detection model for extracting image features.

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Faster R-CNN in conjunction with ResNet101 is used followed by non-maximum supression using IOU threshold and the mean-pooling. The model was pretrained with ImageNet to classify object classes and trained additionally to predict the attribute classes.

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The VQA model of this paper is rather simple. This model utilizes the ‘gated tanh’ layer for non-linear transformation.

So?

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Bottm-up attention is shown to be useful than former methods.

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Up-Down model showed competitive results compared to other models in leader board of VQA 2.0 challenge (ensemble).

Anderson, Peter, et al. “Bottom-up and top-down attention for image captioning and visual question answering.” CVPR. Vol. 3. No. 5. 2018.